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Vaidya, the director of the Rutgers Institute of Data Science, Learning and Applications and a professor of management science and information systems, said crowdsensing technology has been used to track the spread of the flu, but the coronavirus pandemic created an urgency to incorporate privacy enhancements.
Concerns over privacy proved to be one of the barriers in collecting accurate information even as the coronavirus quickly spread through the region.
Vaidya saw the potential to collect data from the public in real time as an alternative to testing that would inform both users and policy makers.
In late April, the National Science Foundation awarded a grant of $199,597 to a team of professors from across different disciplines – Professor Vaidya is working with Rutgers Business School professor Periklis Papaknostantinou as well as Professor Vivek Singh of the School of Communications and Information and Stephanie Shiau from the School of Public Health.
Rutgers Business School Ph.D. student Hafiz Asif and Julian Jarrett from Lutron Electronics are also part of the research team.
In a matter of five weeks, the Rutgers team constructed a website and created a crowdsensing app. The app, which can be downloaded from the website or the Apple App Store, launched July 13. The app will soon be available on Google Play as well. “It guarantees privacy,” Vaidya said. “Using COVIDNearby to report information does not increase the risk to your privacy.”
The secret to assuring privacy lies with the algorithms, according Asif, who worked closely with the professors on the project. The team developed differentially private algorithms to glean insights about the pandemic from the reported data while ensuring privacy of the users.
Vaidya said the app may prove to be a critical tool for communities like university campuses to monitor coronavirus symptoms and manage the spread of COVID-19.
While the app offers a new tool to help protect public health, Vaidya said, it will also allow the professors to learn more about the privacy preferences of individuals. As Asif put it, the coronavirus pandemic provides an unprecedented opportunity to learn about the value people place on privacy in an extreme situation when the information they’re being asked to provide could help save others.
Professor Singh agreed.
"There exists very little empirical evidence to understand how individual privacy decision-making adapts in extreme health emergencies,” he said. “It is critically important to understand the end user’s expectations of privacy in extreme health scenarios to allow for better design of tracking applications in this pandemic and for resilience planning for future extreme events."
